Technical Talks

ABOUT THE TALK

• Workshops

In this talk, we will explore Agentic RAG, a methodology that extends standard Retrieval-Augmented Generation (RAG) applications into powerful AI assistants and agents with advanced capabilities. By equipping LLMs with access to external tools—such as real-time data sources, APIs, or database access—developers can elevate AI systems beyond simple query engines, turning them into sophisticated problem-solvers that adapt to dynamic needs. We will provide a step-by-step walkthrough on how to build Agentic RAG applications, delving into the technical details of a real-world example, and discuss the challenges developers might face, including integration hurdles, handling latency, and designing for robustness.